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Bergmann, R.* ; Weinmann, A.

Inpainting of cycling data using first and second order differences.

Lecture Notes Comp. Sci. 8932, 155-168 (2015)
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Open Access Green
Cyclic data arise in various image and signal processing applications such as interferometric synthetic aperture radar, electroencephalogram data analysis, and color image restoration in HSV or LCh spaces. In this paper we introduce a variational inpainting model for cyclic data which utilizes our definition of absolute cyclic second order differences. Based on analytical expressions for the proximal mappings of these differences we propose a cyclic proximal point algorithm (CPPA) for minimizing the corresponding functional. We choose appropriate cycles to implement this algorithm in an efficient way. We further introduce a simple strategy to initialize the unknown inpainting region. Numerical results both for synthetic and real-world data demonstrate the performance of our algorithm.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Inpainting; variational models with higher order differences; cyclic data; phase-valued data; cyclic proximal point algorithm
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
ISBN 978-3-319-14611-9
Konferenztitel Energy Minimization Methods in Computer Vision and Pattern Recognition
Konferzenzdatum 13 - 16 January 2015
Konferenzort Hong Kong, China
Quellenangaben Band: 8932, Heft: , Seiten: 155-168 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
Begutachtungsstatus